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Schedule maintenance activities for hydrogen fuel cell vehicles are aimed to keep them in better condition in long-term operation. In this paper, we develop a reinforcement learning based schedule maintenance strategy, which is used to comprehensively consider the balance between safety and maintenance cost, so as to find the optimal maintenance strategy. A multi-level framework is established with remaining useful life of key components, fault tree analysis, and logistics cost model to generate an exploration environment that can express the operational stability, the failure rate of components, and the cost of repair and storage. The trained agent combines a deep neural network to explore the optimal strategy under the dynamic reliability of key components. Finite steps are the constraints. Safety rates, maintenance cost, and episode of operation are incorporated into a multi-objective reward function. The hydrogen supply circuit of fuel cell vehicle is simulated via Python. The trained agent is compared with traditional time-based schedule maintenance strategy and corrective maintenance strategy. The results show that the reinforcement learning based schedule maintenance agent has optimized the total reward, cost control and accident rate by 77%, 59% and 5%, respectively, compared with the traditional time-based schedule maintenance strategy. In the safe operation management of fuel cell vehicles, efficient and stable decision-making ability has been achieved. • An adaptive maintenance strategy of deep reinforcement learning is proposed. • An exploration environment of FCV is established. • The deep Q network is proposed to solve the maintenance problem. • The efficient and stable decision-making ability is much better than time-based scheduled maintenance strategy. [ABSTRACT FROM AUTHOR]

Green hydrogen has become more attractive as a fuel for engines to reduce greenhouse gas emissions. By mixing it with natural gas (NG), the modification work on the engine can be minimized but the carbon dioxide emissions from combustion can still be decreased. In this paper, an experimental study was accomplished to investigate the performance of a spark-ignition engine fueled with hydrogen-natural gas blends by either keeping a constant ignition timing or changing it. Up to 25 mol-% hydrogen was mixed into natural gases with different compositions and the methane number and Wobbe index were calculated and compared to the requirements set by Euromot. The results show that up to 15 mol-% hydrogen can be blended into NG to meet the limits of Euromot. However, when 25 mol-% hydrogen was mixed into NG the methane number varied between 56 and 64 depending on the gas composition. This would most likely cause knock for a mixture consisting of higher hydrocarbons but during the executed tests knock was never a problem. Furthermore, it was detected that the methane number alone cannot tell the knock tendency of a gas in a certain engine and an additional condition is needed such as the hydrogen level. An adjusted ignition timing was also preferable compared to a constant one to keep the engine component temperature at a moderate level. • A SI-engine was fueled with different hydrogen-natural gas (H 2 -NG) mixtures. • Wobbe index and methane number (MN) were calculated for all test points. • Efficiency was improved and emissions were decreased with higher hydrogen content. • No tendency of knock when 25 mol-% hydrogen was mixed into natural gas with a low MN. • Additional condition is needed for MN eg. H 2 -level to be sure if knock can happen. [ABSTRACT FROM AUTHOR]

Facing an increasingly hostile ecological environment, the imperative for advancing hydrogen fuel cell vehicles has become more pronounced. This paper establishes a three-dimensional computational fluid dynamics model of a Roots-type hydrogen circulating pump by utilizing the generalized type line equation of the Roots rotor. Delving deep into the intricate interplay of backflow phenomena on the internal flow dynamics and operational efficiency of the Roots-type hydrogen circulation pump across various scenarios. The results reveal that mass flow rate and velocity vary continuously and with the same pulsation frequency as rotation angle or time during a complete rotation cycle. As the rotational speed increases, the number of backflow occurrences decreases, the frequency of backflow currents in the rotor basin decreases, and the temperature rise in both the suction and exhaust chambers decreases. It becomes evident that the rotational speed wields a more profound influence on the Roots pump's performance than temperature: the volumetric and isentropic efficiencies of the Roots-type hydrogen circulating pump decrease by 3.5% and 4.6%, respectively, with increasing temperature, while the volumetric and isentropic efficiencies of the pump increase by 32.6% and 24.0%, respectively, with increasing rotational speed. • The numerical simulation of hydrogen circulation pump using dynamic mesh technique. • Focus on the occurrence and impacts of backflow of hydrogen circulation pumps. • The influence of backflow on internal flow characteristics at different speeds and temperatures. • The general link between return frequency and flow pulsation is discussed in detail. [ABSTRACT FROM AUTHOR]

The ejector-driven hydrogen recirculation system plays an important role in enhancing efficiency of the PEM fuel cell. It's necessary to have deep knowledge of dynamic characteristic of the ejector for optimizing system state, but until now related research is not adequate. In this paper, dynamic characteristic of the ejector for the hydrogen recirculation system of the PEM fuel cell is studied using active periodic pressure excitation. Test plant is set up and active periodic pressure excitation with small amplitude is superimposed on steady pressure at the ejector primary flow inlet. Experiment result shows that in frequency domain, amplitude ratio of dynamic pressure at primary flow inlet to the dynamic delta-pressure, equal to pressure at mixing outlet minus that at backflow inlet, is independent of excitation frequency for each steady operating point. In the complex coordinate, vector of dynamic pressure at primary flow inlet is in parallel with that of dynamic delta-pressure, for all frequencies and for all stable operating points. Furthermore, amplitude ratio of dynamic pressure at primary flow inlet to dynamic delta-pressure exhibits linearity with entrainment ratio of the ejector for all stable operating points. Experiment on the 120 kW fuel cell system validates the same dynamic characteristic. • Dynamic characteristic of ejector studied using active periodic pressure excitation. • Ratio of dynamic primary-flow pressure to delta pressure independent of frequency. • Vector of primary-flow pressure in parallel with that of the dynamic delta-pressure. • Ratio of primary-flow pressure to delta pressure in linearity with entrainment ratio. [ABSTRACT FROM AUTHOR]

Among the global carbon emissions in different fields, the carbon emissions in the transportation sector account for more than 1/4. Only the development of passenger car technology makes it difficult to achieve the climate goals. E-bike is considered to be one of the effective solutions. Hydrogen energy, as one of the representatives of new energy, has the advantages of cleanliness, high efficiency, and high energy density. Therefore, in this paper, a long-range hydrogen-electric hybrid bike and its energy management strategy are designed to achieve optimal performance. Herein, two energy management strategies, including the threshold-based and fuzzy logic optimized threshold-based strategy, are designed and compared by evaluating the parameters of equivalent hydrogen consumption, state of charge fluctuation, and the final state of the control system. The results show that with an initial SOC of 50% for Li-ion battery, the fuzzy logic optimized threshold-based strategy reduces equivalent hydrogen consumption by up to 16% compared to the threshold-based strategy. Besides, the fluctuation of the Li-ion battery's state of charge could be reduced by up to 54.7%, indicating that the fuzzy logic optimized threshold-based strategy is a promising energy management strategy for fuel cell hybrid E-bike. [Display omitted] • A long-range hydrogen-electric hybrid E-bike with metal hydride hydrogen storage is designed. • A fuzzy logic optimized threshold-based energy management strategy (EMS) is proposed. • Li-ion battery SOC fluctuations could be reduced by up to 54.7% via fuzzy logic optimized EMS. • Fuzzy logic optimized EMS shows self-adaptability and economic H 2 consumption for hybrid E-bike. [ABSTRACT FROM AUTHOR]

In the contemporary global discourse on environmental and developmental issues, the dual challenges of sustainable green energy and water supply stand paramount. These elements are vitally intertwined with the socio-economic vitality of the world. Notably, regions plagued by freshwater scarcity are increasingly turning to desalination which consists of a reliable and unconventional water source. The intersection of renewable energy with desalination and water purification processes presents a compelling synergy. This approach is particularly pertinent in areas where freshwater shortages coexist with abundant solar energy availability. Additionally, these technologies boast the advantage of low operational and maintenance costs. This paper delves into the design, optimization and financial analysis of a novel, standalone hybrid energy system, integrating photovoltaic and fuel cell technologies, for an agriculture farm situated in Kairouan, Tunisia. Unlike conventional systems, this model foregoes battery storage in favour of hydrogen storage, generated through water electrolysis powered by solar energy. This system harnesses solar energy for direct electrical power generation and hydrogen gas production. A segment of the generated electricity is allocated to electrolysis for green hydrogen production. In times of solar unavailability, the stored hydrogen is reconverted to electricity via a fuel cell. An intriguing aspect of this system is the utilization of saline well water, which, due to its high salt content, necessitates purification through desalination to prevent damage to the electrolysis unit and to render it suitable for agricultural irrigation. [Display omitted] • The production of green hydrogen, water and electricity for agriculture farm in Tunisia is analyzed. • The Levelized cost of green hydrogen produced in the PV farm is 2.25 €/kg. • A PV hydrogen Farm station with a capacity of 140 kW produces 1991 kg of green hydrogen and 235 MW h of electricity yearly. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the relationship between the suction, discharge flow control and self-designed co-rotating scroll hydrogen circulation pump (CSHCP) aerodynamic performance and irreversible flow loss. The effect of five suction angles and five discharge spoiler positions on the performance and flow loss of a CSHCP was firstly revealed using the computational fluid dynamics (CFD) three-dimensional numerical simulation method combined with entropy production (EP) theory and omega vortex identification methods. The optimized suction angle and discharge spoiler position of CSHCP were identified through comparing with isentropic and volumetric efficiency, EP, vortex distribution and flow pulsation intensity. Subsequently, the performance and flow loss difference of CSHCP are further distinguished before and after optimization of suction and discharge spoiler structure under designed or variable rotational velocities. The results demonstrate that the optimized suction angle and discharge spoiler position angle are 22.5° and 45°, respectively. After the combination optimization of suction and discharge spoiler structure, the total EP and discharge temperature pulsation intensity of CSHCP are reduced by about 13.2% and 67.5% respectively. The research results provide a reference for the efficient and stable operation of HCP for fuel cell system. • A self-designed co-rotating scroll hydrogen circulation pump is studied. • Five suction angles and five discharge spoiler positions are compared. • Aerodynamic performance and flow loss of different structures are revealed. • Its performance under variable rotational velocities is distinguished. [ABSTRACT FROM AUTHOR]

For saving fuel and extending the fuel cells (FC)/battery lifetime, this paper proposes a real-time cost-optimal predictive energy management strategy of FC hybrid electric vehicles based on continuation/general minimal residuals (C/GMRES) algorithm. To ensure the preferable continuation for algorithm application, the continuity method is proposed for accurate model approximations. The external penalty method is employed to transform the inequality constraints as an equivalent index cost. Then, the continuous and unconstrained model predictive control problem is reformulated, and the C/GMRES algorithm is proposed for real-time optimization. Given the output, the expected FC control command can be decided by the designed postprocessing rules. The performance of the proposed strategy is validated under simulations and hardware-in-the-loop (HIL) tests. The results manifest that the proposed strategy can effectively save the total cost for the predictive horizon of 5s–60s even when the neural network-based predictive velocity is adopted. Besides, compared with the interior point method, the proposed C/GMRES algorithm achieves similar solving effects while exhibiting more than 100 times computing efficiency. In addition, the execution time of the proposed strategy in each step is less than 1.2 ms under HIL tests, indicating its real-time applicability. • State of health for fuel cells and battery are modeled and optimized. • Continuity method of health-aware system model is proposed. • Real-time optimization algorithm is proposed for this highly nonlinear problem. • Results about horizon length and predictive errors are gained and discussed. • HIL test verifies the control effects and real-time applicability. [ABSTRACT FROM AUTHOR]

Precooling gaseous hydrogen fuel to a cold temperature before refueling a heavy-duty (HD) hydrogen fuel cell electric vehicle (HFCEV) is essential to avoid overheating the vehicle tank, as well as achieving a high state of charge (SOC). Because a large volume of hydrogen is dispensed during each fill, the need for a shorter fill time amplifies the need to precool each load for refueling a HFCEV. Thus, the design and operation of a precooling unit (PCU), as well as the associated capital and operating costs, plays a pivotal role in any plans for heavy-duty hydrogen refueling stations. In this paper, we present a thermodynamic and technoeconomic analysis of a PCU in a gaseous hydrogen refueling station (HRS) for HD HFCEVs. By employing Argonne National Laboratory's hydrogen station cost optimization and performance evaluation (H2SCOPE) model, the refueling of 50 kg of hydrogen on-board type IV tank at ambient temperatures of 15–45 °C and varying fill rates is simulated. The required degree of precooling temperature to obtain either 100% or the maximum possible SOC is obtained from the simulation. Additionally, the simulation results demonstrate that the average flow rate of hydrogen is approximately 40% lower than the maximum flow rate during a typical fill; which motivates further evaluation of the instantaneous hydrogen mass flow rate profile and suggests the scope of improving precooling unit design. Accordingly, a hybrid strategy of precooling hydrogen has been proposed to address the cooling load by sizing the refrigeration unit for the average flow rate of hydrogen, while supplementing the above average peak hydrogen flow cooling load through thermal buffering. The combined technique enables the downsizing of the original PCU capacity by 25–40% and demonstrates a potential cost reduction of the PCU by approximately 30%, which translates to an installed cost reduction of ∼$125,000 per dispenser. • Hydrogen fill rate during refueling has a strong influence on the precooling load. • Bell-shaped profile of the fill rate advises a scope of improving precooling. • Hybrid strategy of on-demand cooling aided with partial thermal buffer is proposed. • The hybrid precooling approach downsizes the refrigerator capacity by 25–40%. • A potential reduction in the capital cost of precooling unit is 30%. [ABSTRACT FROM AUTHOR]

The paper reports on carbon coatings deposited by accelerated C 60 ion beam irradiation onto the VT1-0 titanium alloy surface at different substrate temperatures, considering potential applications in fuel-cell bipolar plates. We identified the temperature range for forming a conductive carbon nanocomposite coating (CNC) at different accelerating voltages (U a). The obtained CNC consists of graphite nanocrystals embedded in an amorphous diamond-like matrix. The nanocomposite containing ∼40% of sp 3 bonds is formed at T s = 300–400 °C under U a = 6 kV. The increase in accelerating voltage to 8 kV reduces the temperature of the nanocomposite formation to T s = 200 °C. Interface contact resistance (ICR) of a CNC coated titanium plate decreases to 2.6 ± 0.7 mOhm⋅cm2 at a sealing pressure of 1.5 MPa, which is close to carbon paper – graphite contact resistance. This low ICR value persists after prolonged corrosion tests. Tribological studies established high wear resistance and high adhesion of CNC to titanium substrate, showing potential for stable operation of coated bipolar plates in mobile applications. CNC allows to overcome the limitation of corrosion-caused ICR increase, which makes CNC-coated titanium a promising candidate to substitute gold-coated stainless steel as a raw material for bipolar plates of proton-exchange membrane fuel cells. • Nanocomposite carbon coatings are deposited on titanium by accelerated C 60 ion beam. • The interface contact resistance obtained is as low as 2.6 ± 0.7 mOhm⋅cm2. • Coated samples exhibit a stable low corrosion current for a long period of time. • Coatings show high adhesion to titanium and high wear resistance. [ABSTRACT FROM AUTHOR]

Road freight transport on hilly routes represents a significant challenge for the advancement of fuel cell electric trucks because of the high-performance requirements for fuel consumption, vehicle lifetime, and battery charge control. Therefore, it is essential to optimize the vehicle design and energy management, which greatly influence the driving performance and total cost of ownership. This paper focuses on the cost-optimal design and energy management of fuel cell electric trucks, considering five key influencing factors: powertrain component sizing, driving cycle, vehicle weight, component degradation, and market prices. The cost optimization relies on a novel predictive energy management scheme based on dynamic programming and the systematic calibration of control parameters. The paper analyzes the simulation results to highlight three main findings for fuel cell electric trucks: 1) cost-optimal energy management is essential to define the best trade-off between fuel consumption and component degradation; 2) the total cost of ownership is significantly influenced by component sizing, driving cycles, vehicle weight, and market prices; 3) predictive energy management is highly beneficial in challenging road topographies for substantial cost-saving and lower component size requirements. [Display omitted] • Investigation on total cost of ownership of heavy-duty fuel cell electric vehicles. • Optimal vehicle design and control in demanding routes for performance requirements. • Energy management optimization for minimum ownership cost in realistic driving scenarios. • Trade-off analysis between fuel consumption and expected powertrain components life. • Significant benefits of predictive energy management in challenging road topographies. [ABSTRACT FROM AUTHOR]

Membraneless microfluidic fuel cell (MMFC) has potential application prospects in micro-devices due to the characteristics of considerable output performance, superior cleanliness and easy miniaturization. Whereas, the performance of MMFC is restricted by the mass transfer of two-phase flow, which manifests as the inefficiency transportation in liquid phase and obstruction of gas phase. This paper proposes a novel sinusoidal corrugated channel (SCC) for MMFC though developing a three-dimensional two-phase model by coupling the multi-physics field to improve the cell performance in mass transfer, and further studies the two-phase flow characteristics of geometric parameters of SCC, including the amplitude A and angular frequency ω. Based on the optimal configuration in A of 0.5 mm and ω of 3 rad s−1, compared with the conventional straight channel, the increase ratios of maximum current density, power density, fuel utilization are 13.69%, 8.39% and 13.72%, respectively. Additionally, the gas volume fraction at the maximum power density decreases by 12.62%. This paper provides new insights and theoretical foundations for the study of MMFC flow field configurations, and furnishes references for the mass transfer intensification. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell (PEMFC) is one of the most promising power energy sources in the world, and its mechanism research has become the main starting point to improve the comprehensive performance of fuel cells. The gas diffusion layer (GDL) of a proton exchange membrane fuel cell has a significant impact on the overall performance of the cell as an important component in supporting the catalytic layer, collecting the current, conducting the gas and discharging the reaction product water. In this paper, a three-dimensional two-phase isothermal fuel cell model is established based on COMSOL, the gradient porosity of the GDL, thickness of the GDL, operating voltage and working pressure of proton exchange membrane fuel cell are analyzed, the consistency problem of fuel cell performance improvement and life extension that is easily overlooked in numerous studies is found. On this basis, a neural network proxy model is constructed through a large amount of data, and a multi-objective genetic optimization algorithm based on the compromise strategy of recombination optimization is proposed to optimize the uniformity of fuel cell power and oxygen molar concentration distribution, which improves the performance of the fuel cell by 1.45% compared with the power increase when it is not optimized. At the same time, the uniformity of oxygen distribution is improved 10.28%, which makes the oxygen distribution more uniform, prolongs the life of the fuel cell, and fills the gap in the optimization direction of the comprehensive performance of the fuel cell. • The three-dimensional two-phase isothermal geometric model of PEMFC is established based on COMSOL. • Establish the gradient porosity equation of cathode gas diffusion layer. • Establish a neural network proxy model to replace COMSOL fuel cell mechanism model. • A multi-objective genetic optimization algorithm based on recombination optimization compromise strategy is proposed. • This paper discusses the easily overlooked issue of consistency in fuel cell performance improvement and life extension. [ABSTRACT FROM AUTHOR]

In recent years, fuel cells have attracted more and more attention in the energy field. However, accurate evaluation of durability is one of the key aspects of large-scale commercial application of fuel cells. The data-driven method has good fitting performance for predicting remaining useful life (RUL) at complex and nonlinear systems. In this paper, Cycle Reservoir with Jump with multi-inputs and multi-outputs (MIMO-CRJ) is proposed to further improve the fitting speed and reduce the complexity of the system which improved the structure of echo state network (ESN). Different from the previous method that only uses voltage to predict the voltage, this paper considers stack current, temperature and pressure, reactant flow rate in fuel cell operation as input variables, and extracts more degradation information to predict the voltage trend. Experimental results show that MIMO-CRJ has better performance than Cycle Reservoir with Jump with single -inputs and single-output (SISO-CRJ) and ESN networks under both static and quasi-dynamic current conditions. • The multi-input Cycle Reservoir with Jump network is proposed for prognostics. • The proposed model can be used for remaining useful life on the static current and dynamic current experiments. • The MIMO-CRJ is used for short-term prediction and long-term prediction of PEMFC. [ABSTRACT FROM AUTHOR]

The paper proposes the analysis of four different scenarios of renewables penetration (40%, 60%, 80%, and 100%) with the most affordable generators: photovoltaic panels and wind turbines. The synergy of two storage technologies, such as Li-Ion batteries and the hydrogen power-to-power solution (electrolyzer, H 2 tank, and fuel cells), is evaluated to ensure the balance of the power-grid. The paper discusses the numerical Trnsys-based modeling of the smart grid. A detailed performance evaluation of each component, according to operational maps provided by manufacturers, has been performed to meet an electrical load (10 MW peak - 54 GW h annual). The results of the analysis show the crucial role of the H 2 system in the goal of achieving a higher renewable fraction, mainly due to the possibility of seasonal storage without the self-discharge limitation of batteries. In the 100% renewable solution the contribution of H 2 is equal to 30% of the electric load. • The synergy of Li-Ion batteries and hydrogen is evaluated to ensure grid balance. • Hydrogen integration has been evaluated in the path to 100% renewable energy. • The optimum solution is a tradeoff between renewable share and system cost. • A fully renewable system would cost $0.42/kWh with a 30% hydrogen contribution. • Hydrogen power-to-power system is strongly limited by high cost. [ABSTRACT FROM AUTHOR]

[Display omitted] • Atomic Pt clusters are simply fabricated on Au dendrite for FAOR. • The isolated Pt sites on Au demonstrated high selectivity for direct FAOR pathway. • Extremely high FAOR mass activities are obtained in half cell and single cell test. • The CO chemisorption analysis confirmed the stability of isolated Pt sites after FAOR. The minimization of Pt loadings on Au via facile fabrication methods remains a grand challenge in the development of commercially viable electrodes for direct formic acid fuel cells. Herein, we report a simple electrochemical strategy to prepare atomic Pt clusters on Au dendrites supported by carbon paper (CP) as a gas diffusion electrode. At highly negative deposition potentials, Pt deposition is autonomously quenched by immediate adsorption of discharged proton (H) on Pt surface, while highly roughened Au dendrites lead to resistance–capacitance delay for the transient cathodic current. As a result, the suppressed Pt nucleation and self-terminated Pt growth allows for the formation of isolated Pt sites on Au dendrites. The Pt/Au/CP with an ultra-low Pt loading of 5.0 μg Pt /cm geo 2 demonstrates high selectivity for direct pathway of formic acid oxidation reaction (FAOR), owing to the ensemble effect. A gradual increase of FAOR activity is observed during cycling test and then, the 20 cycled Pt/Au/CP shows remarkable FAOR activity in half-cell test, exceeding state-of-the-art Pt-Au catalysts. Theoretical calculation indicates that the stabilized intermediate on Pt clusters accelerates the direct FAOR pathway. CO chemisorption analysis reveals that the isolated Pt sites remain stable throughout the reaction. Single cell test for direct formic acid fuel cell with 20 cycled Pt/Au/CP anode demonstrate two-order higher Pt mass activity and mass power density, compared with values reported in recent literature. [ABSTRACT FROM AUTHOR]

Short-term performance degradation prediction is significant for fuel cell system control and health management. This paper presents a hybrid deep learning method by combining the convolutional neural network (CNN) and long short-term memory (LSTM) network to predict the short-term degradation of a 110 kW fuel cell system used for the commercial vehicle. First, the complete ensemble empirical mode decomposition (CEEMD) is applied to decompose the nonlinear and non-stationary voltage sequence extracted by the sliding window into modality sequences with different characteristic time scales. Then, these modality sequences are input into the corresponding CNN-LSTM for voltage prediction. Experimental results show that the proposed CNN-LSTM can reduce the root mean square error (RMSE) by 13.55% and 34.40%, respectively, compared to the single CNN and LSTM because it combines the spatial feature extraction ability of CNN and the powerful prediction ability of LSTM. Furthermore, the CEEMD–CNN–LSTM can reduce RMSE by 36.92% compared to CNN-LSTM since the impact of exogenous factors on the recoverable decay and intrinsic decay of the fuel cell can be separated easily for better model learning. The CEEMD–CNN–LSTM is also compared with other recently published deep learning models based on the same data set, and the results show that the prediction framework in this paper has higher accuracy. • Aging data of a 110 kW fuel cell system is used for model training and validation. • Complete ensemble empirical mode decomposition is applied to decompose voltage time. • Convolutional neural network and long short-term memory network are combined. • The prediction result under the delay condition of 5 h–6 h is still referential. [ABSTRACT FROM AUTHOR]

In this paper, a three inputs six-phase Interleaved Boost Converter (IBC) is proposed and designed for Fuel Cell (FC) systems, where the different Polymer Electrolyte Membrane Fuel Cells (PEMFC) systems are employed to validate. Considering that the selected converter is composed of three two-phase IBCs connecting in parallel, it shows many superiorities in topology, such as simple structure, high scalability/flexibility, easy maintenance and good fault-tolerant ability. The whole design process containing the selection of phase numbers, parameters design of the converter's components and steady-state operations analysis is focused in this paper. To further validate the correctness of the designed converter, a test bench is established based on dSPACE1104 , where the issue of the implementation of six-PWM signals from dSPACE1104 is analyzed and a feasible solution is proposed. Last, experimental results are shown by performing the load disturbance rejection, the variable reference voltage and the PEMFC system's failure based on the designed Double-Loop Super-Twisting Sliding Mode (DL-STSM) controller. • Three inputs six-phase interleaved boost converter is designed for fuel cell systems. • The designed converter shows high scalability and good fault-tolerant ability. • A solution is proposed to address the achievement of six-PWM signals in dSPACE1104. • Experimental verification of the designed converter with different fuel cell systems. • Load disturbance rejection, variable reference voltage and FC failure are validated. [ABSTRACT FROM AUTHOR]

[Display omitted] • GDLs with patterned hydrophobicity have been investigated for PEFCs. • Three different wettability patterns have been proposed. • Their effect on the fuel cell performance was compared to the uniformly treated GDLs. • GDLs with patterned hydrophobicity showed superior fuel cell performance. • The patterned GDLs demonstrated less oxygen transport resistance. Flooding of the cathode due to water accumulation is one of the biggest limiting factors in the performance of polymer electrolyte fuel cells (PEFCs). This study therefore attempts to solve this issue by fabricating gas diffusion layers (GDLs) with differently patterned hydrophobic regions. The GDLs in three different patterns (triangular, diamond, and inverted-triangular) were prepared by brushing a Polytetrafluoroethylene (PTFE) solution onto commercial carbon papers through a mask and tested in PEFCs. The patterned GDLs results in superior performance in all cases compared to a uniformly PTFE-treated GDL. Notably, the oxygen transport resistance is significantly reduced, indicating that the water accumulation in the cathode is avoided. This is attributed to the patterned hydrophobicity gradient providing distinct pathways for water and oxygen. The GDL with triangular patterning displays the highest peak power density, due to the fact that the untreated less hydrophobic region is in direct contact with the cathode outlet in this case, facilitating the removal of excess liquid water. Overall, the study confirms that the GDLs with patterned hydrophobicity could be used to enhance the performance of commercial PEFC systems by facilitating water management, potentially leading to improved efficiency and durability. [ABSTRACT FROM AUTHOR]

• Two-dimensional model considering interface and compression effect is developed. • Thermal responses under gas channel and land are significantly different. • Interface resistances greatly affect thermal response and performance. • Phase change can cause temperature overshoot/undershoot as load changes. • An optimal assembly pressure is found with consideration heat transfer. The improper thermal response is one of the main causes of proton exchange membrane fuel cell degradation. In this study, a two-dimensional, non-isothermal, two-phase transient fuel cell model has been established combined with newly measured experimental data. This model fully incorporates the land and gas channel (GC) of the bipolar plate, comprehensively accounting for the electrical contact resistance (ECR) and the thermal contact resistance (TCR) at the carbon paper/land interface, as well as the changes of carbon paper structure and electrical/thermal resistance induced by assembly pressure. By simulation, the impacts of interface resistance, working conditions, and assembly pressure on the thermal responses under land and GC are systematically investigated. The existence of TCR is found to increase the two regions' temperature significantly, while ECR only slightly raises it by generating a surface heat source. Furthermore, uneven distribution, ununiform fluctuation, and rapid overshoot/undershoot of temperature are observed in the two areas during overload and change load operations. It is mainly caused by the different distributions and responses of reaction and phase change at various locations. In the end, the average temperature is found to fall significantly and reach a new steady fastly with the increase of assembly pressure due to the reduction of bulk and interface thermal resistances of carbon paper. However, performance degradation and hot spot temperature rise are further observed if the pressure is too high. To balance performance and heat transfer, we should choose an optimal assembly pressure. [ABSTRACT FROM AUTHOR]

The hybrid microgrid system (HMS) can offer a cost-effective system for isolated areas by optimizing energy sources. This paper presents a design approach for a wind turbine (WT)/hydrogen HMS with eight alternative small horizontal-axis WTs and arrives at a conclusion based on the total annual cost (TAC), cost of energy (COE), and the loss of power supply possibility throughout the project's life cycle. The effect of adding solar panels to the HMS is investigated in different scenarios. The modified bio-inspired optimization algorithm with high efficiency is used, and its results are validated using an original particle swarm optimization in different unavailability levels. Owing to a sensitivity analysis that utilized the wind speed, load demand, and interest rate, the potential of the proposed algorithm to achieve the optimal off-grid HMS design was highlighted. Among the investigated systems (more than 16 systems), the Winds WT/hydrogen energy/solar configuration with $11,952 TAC and 0.3458$/kWh COE has the minimum cost while setting the unavailability level to 2%. In addition, the adding of solar panels, variation of small WT models, wind speed, load demand, and interest rate levels have a significant impact on COE value and number of components. • A design approach for a wind/hydrogen system with various small horizontal-axis WT is proposed. • The effect of adding solar panel to the hybrid system is investigated in different scenarios. • The modified bio-inspired optimization algorithm with high efficiency is proposed. • The algorithm results are validated using an original PSO in different reliability level. • Sensitivity analysis to account for uncertainties in the optimal system is investigated. [ABSTRACT FROM AUTHOR]

This paper endeavors to utilize the numerical modeling method to evaluate the energy, economic, and environmental performances of a new hybrid PV-FC system for green hydrogen and electricity production. The proposed system consists of photovoltaic panels, fuel cells, an electrolyzer, a converter, and a hydrogen storage tank. A robust techno-enviro-economic (3E) analysis is conducted through comprehensive modeling for the system components using MATLAB/Simulink®. In this validated model, the essential parameters have been calculated: PV plant power, area and efficiency, electrolyzer efficiency, flow rate and power, stack power, area and efficiency, total LCOE of the integrated components, and CO 2 emission reduction. Moreover, the NSGA-II coupled with TOPSIS decision-making approach and Gaussian Process Regression machine learning method with selection kernel function are also utilized as a novel inclusion for the prediction and optimization of the 3E performances of this hybrid system. To obtain a multidimensional view of the optimization, six key decision variables of total stack power, fossil fuel-based generator energy, total CO 2 emissions coming from hydrogen production, total FC system voltage, module area, and number of PV modules have been adopted. The optimization problem encompasses maximizing the total fuel cell stack power and carbon emission reduction, while simultaneously minimizing the total stack area and levelized cost of energy. The simulation outcomes reveal that the stack can reach its maximum output power of 350 kW when operating temperatures are between 40 °C and 55 °C and there are more than 380 cells in the stack. Also, the LCOE was found to be less than $2/kWh for solar radiation above 250 W/m2 and PV outputs reaching 100 W. Further, Increasing FCs from 10 to 400 reduces CO 2 emissions by roughly 13% at 100 °C. Ultimately, the optimal configuration of the system yields stack power of 1589 kW, a total stack area of 269.9 m2, and total CO 2 emission reduction of 1268 ton CO2 , respectively. • Robust 3E analysis using MATLAB-based techno-environmental-economic study. • ML tool using GPR and GA optimization method used for performance optimization. • LCOE is less than $2/kWh for solar radiation above 250 W/m2 and 100 W PV output. • The PVFCEHST model exhibits a high degree of reliability and a robust integrated model. • FC power efficiency reaches 60% when operational temperature is between 40 and 55 °C. [ABSTRACT FROM AUTHOR]

Hydrogen-powered aviation is becoming a promising and competitive aviation power selection for developing zero-emission aerial vehicles. The current options for hydrogen aviation power include hydrogen gas turbines, hydrogen fuel cells, and hydrogen hybrid power. Among them, hybrid power offers a greater competitive advantage as it possesses the advantages of both gas turbines and fuel cells and exhibits higher efficiency levels. Nonetheless, there is still a lack of research on thermal management strategies to improve hydrogen-powered hybrid system efficiency. In this paper, a method that integrates thermal management and topology optimization is proposed to realize the energy-efficient system topology design of the hydrogen-powered hybrid system. Initially, based on the existing topology of the hydrocarbon fuel hybrid system, the overall design of the thermal management architecture of the hydrogen fuel hybrid system is improved, and an integrated calculation method for coupling subsystems such as fuel cells, gas turbines, and component cooling is established. Afterward, a method for optimizing the topology is put forward to improve the flow of mass and energy among components in the hybrid system, and the topology with higher energy efficiency is determined through exergy analysis. Ultimately, through parametric analysis of the optimized hybrid system performance, it is obtained that when the fuel cell fuel utilization rate is 80 %, an energy conversion efficiency of 69 % can be achieved during the cruise phase. • A thermal management system for hydrogen-powered hybrid systems is proposed. • Topology optimization of the hybrid system structure is performed for the first time. • Detailed exergy analysis is performed to determine system performance. • The optimized system can achieve an efficiency of 69 %. [ABSTRACT FROM AUTHOR]

The rapid, safe, and adequate refueling for hydrogen-based fuel cell vehicles relies on deep pre-cooling on the station side, which brings significant energy consumption. Step cooling is an ideal solution for the occasion with a large temperature drop. In this paper, a novel pre-cooling system is proposed by incorporating two-temperature evaporation to realize step cooling in the hydrogen refueling station. The pre-cooling load, system performance, and energy-saving potential are investigated under variable storage configurations and working conditions. The results show that the integral pre-cooling load increases linearly with the ambient temperature. However, the load share and the system performance are affected by the hydrogen intermediate temperature, the optimal value of which exhibits a nearly linear relationship with the ambient temperature. The novel system can save up to 30.2 % electricity relative to the conventional system with a single evaporator. [ABSTRACT FROM AUTHOR]

One of the effective strategies to pursue the highly durable high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) is to introduce inorganic fillers to the phosphoric acid-doped polybenzimidazole (PA/PBI) membranes. Among the inorganic fillers, phosphates such as phosphosilicate are effective in mitigating acid loss at elevated temperatures (200–300 °C). In this paper, the effect of in situ formed phosphosilicate on the performance and stability of SiO 2 /PA/PBI composite membranes is studied in detail. The mechanical properties and electrochemical performances of the in situ formed SiO 2 /PA/PBI membranes depend strongly on the content of in situ formed Si 5 P 6 O 25 fillers and its distribution and microstructure in the membrane. Such in situ formed SiO 2 /PA/PBI composite membranes show a high conductivity of 53.5 mS cm−1 at 220 °C. The assembled single cell shows a maximum peak power density (PPD) of 530.6 mW cm−2 and excellent stability at elevated temperature of 220 °C for over 130 h. The exceptional stability at 220 °C is most likely due to the existence of predominant amorphous phosphosilicate phases in the in situ formed SiO 2 /PA/PBI composite membranes, which inhibits the evaporation and leaching of PA at elevated temperatures. The results indicate the practical application of in situ formed SiO 2 /PA/PBI composite membranes for HT-PEMFCs. • In situ formation of predominantly amorphous phosphosilicate phases in SiO 2 /PA/PBI composite membranes. • The as-synthesized SiO 2 /PA/PBI membrane based PEMFCs can operate at elevated high temperatures of 200–250 °C. • The composite membranes based PEMFCs show high performance and excellent stability at 220 °C. • The in situ formed predominantly amorphous phosphosilicate phases can effectively contain PA at high temperatures. [ABSTRACT FROM AUTHOR]

Improving the commercial fuel cell system efficiency is critical to reducing hydrogen consumption and improving the operational economy. This paper studies the power consumption pattern of the air supply subsystem, the most power-consuming auxiliary components, aiming to improve the system's efficiency. A method was proposed to get the extremum of the system net power by optimizing the oxygen excess ratio and cathode pressure. Mathematical models describing the fuel cell stack and air supply subsystem power characteristics were developed based on the mechanism analysis and estimation of unknown parameters. Then, a system net power model for energy efficiency optimization was developed. The operating conditions for optimal efficiency at a specific current density can be obtained by numerical calculation. To verify the method's effectiveness, a series of experiments were conducted, and the results show that the proposed method can maximize system net power output at various current density conditions. Compared with the conventional oxygen excess rate based one-dimensional optimization, the two-dimensional method can improve system efficiency by 2.06%, offering a good application prospect. • A mathematical model describing the fuel cell stack and air supply subsystem power characteristics was developed. • An energy efficiency optimization method based on the oxygen excess ratio and cathode pressure is proposed. • The operating conditions for optimal efficiency can be obtained by numerical calculation. • Maximum efficiency improvement of 2.06% can be achieved compared with One-dimensional optimization. [ABSTRACT FROM AUTHOR]

Sustainable aviation is a key part of achieving Net Zero by 2050, and is arguably one of the most challenging sectors to decarbonise. Hydrogen has gained unprecedented attention as a future fuel for aviation, for use within fuel cell or hydrogen gas turbine propulsion systems. This paper presents a survey of the literature and industrial projects on hydrogen aircraft and associated enabling technologies. The current and predicted technology capabilities are analysed to identify important trends and to assess the feasibility of hydrogen propulsion. Several key enabling technologies are discussed in detail and gaps in knowledge are identified. It is evident that hydrogen propelled aircraft are technologically viable by 2050. However, convergence of a number of critical factors is required, namely: the extent of industrial collaboration, the understanding of environmental science and contrails, green hydrogen production and its availability at the point of use, and the safety and certification of the aircraft and supporting infrastructure. [Display omitted] • Brief insights of previous research (Lockheed 1970s, Tupolev-155, Cryoplane 2000s). • Findings of recent projects (FlyZero, ENABLE-H2, CHEETA, AIA, NAPKIN) discussed. • State of the Art status and future projections of enabling technologies presented. • Fuel cell propulsion system could enable regional electric aircraft by 2035. • Hydrogen-burning turbines crucial for mid to long-haul aircraft. [ABSTRACT FROM AUTHOR]

The microchannels on the bipolar plates (BPPs) of a proton exchange membrane fuel cell (PEMFC) have various functions. Increasing the microchannel depth leads to an increase in the efficiency of the fuel cell. In this paper, metallic BPPs of the PEMFC made of commercial pure titanium (CP-Ti) with an initial thickness of 0.1 mm are manufactured using the stamping process. First, after performing the process using experimental tests and finite elements (FE) simulation, the accuracy of the numerical results is confirmed. In the following, using the FE model and considering process parameters including die clearance, forming speed, and sheet/die friction coefficient, a set of experiments is implemented using the response surface method (RSM). The results of the filling rate are obtained from the experiments and a regression model is established to predict the filling rate of the microchannel. Then, four meta-heuristics methods including artificial bee colony optimization (ABCO), genetic algorithm (GA), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are used to estimate the formability of the CP-Ti BPPs. According to the results, the ANFIS model with an error of 0.0062 × 10−3 % compared to experiments is more reliable to predict the filling rate in the stamping of the CP-Ti BPPs. • The titanium bipolar plates for proton exchange membrane fuel cells are manufactured using stamping. • Effect of clearance, forming speed, and friction coefficient on the maximum filling rate of the stamped plates investigated. • Meta-heuristics methods are applied to estimate the formability of the stamped bipolar plates in terms of filling rate. [ABSTRACT FROM AUTHOR]

This paper investigates an innovative study on the performance of a hybrid condensing boiler-fuel cell micro-cogeneration system for single residential applications. It combines experimental and dynamic numerical investigations including renewable energy for green hydrogen production and solid storage. Basing on the hourly measurements for a typical winter day, a dynamic model was developed and validated against different home heating need. Highlighting the influence home energy needs on fuel cell operating mode, it shows that single homes with low energy demand led to reduce the fuel cell's yearly operation below 50 %. In low-energy homes, a reduction in fuel cell size led to an increase in yearly operation to 60-70 % and achieved a 55 % electrical coverage rate. The integration of metal hydride hydrogen solid storage, powered by renewable sources, is emphasized. This setup increases heat demand, influencing fuel cell operation. In winter season, fuel cell operated for an average of 611 h, compared to 61 h in summer. System efficiency averaged 91 % annually, peaked at 95 % in summer, and sustained 93 % when both FC and condensing boiler were switched on. [Display omitted] • Modeling of a hybrid Boiler-Fuel Cell MCHP system for residential energy management. • Calibration of the FC-MCHP model using experimental data from a real MCHP unit. • Electrical and thermal coverage of the FC-MCHP unit with green hydrogen production and storage under different scenarios. • Strategies for optimal hydrogen consumption in in residential application. • Impact of solid-state hydrogen storage on FC-MCHP consumption and thermal management. [ABSTRACT FROM AUTHOR]

The use of hydrogen fuel cell vehicles is an important way to achieve carbon emission reduction in China's commercial vehicle field. The development of the hydrogen automobile industry needs policy guidance. To determine the characteristics and effects of China's hydrogen automobile industrial policy, this paper first uses a text mining method to analyze policy characteristics from three aspects: potency rank, policy subject and policy objectives. Then, from the perspective of policy tools, a policy quantitative system and standards are constructed to quantify the policy. Then, the sales data of hydrogen fuel cell vehicles from August 2018 to December 2022 were collected to empirically analyze the effect of the policy. The results showed that policy comprehensiveness significantly promoted the use of hydrogen fuel cell vehicles, but the effects of the different policy tools differed. Finally, some policy suggestions are proposed for the development of the hydrogen automobile industry. • China's hydrogen vehicle industry policy focuses on technology upgrading and application demonstration. • The use of hydrogen fuel cell vehicles is the most concerned industrial chain link in the policy. • Policy comprehensiveness has a significant positive effect on the promotion of hydrogen fuel cell vehicles in China. • Different policy tools play different roles, with supply-based policy tools and demand-based playing a more prominent role. [ABSTRACT FROM AUTHOR]

Oxygen stoichiometry (OS) and stack temperature (ST) significantly affect the output performance and durability of proton exchange membrane fuel cells. This paper investigates the prescribed performance tracking control strategy of OS and ST under external disturbances, modeling errors, actuators faults and limited communication resources. The total disturbances are compensated by a variable-bandwidth extended state observer to simplify the control design and enhance the system robustness. To tolerate excessive disturbances and relax the strict requirement on the initial conditions, a new event-triggered adaptive sliding mode controller that integrates modified dynamic performance constraints and nonsingular error transformation is developed to ensure the user-designed transient and steady-state performance constraints, while saving the communication costs and avoiding the chattering and jump in control signals. The numerical validation results under combined working scenarios indicate that the proposed controller always ensures the preset error constraints and possesses superior performance in tracking the optimal OS value 2 and the optimal ST value 353.15K than other three representative controllers, with the integral absolute errors of 0.732 for OS tracking and 12.94 for ST tracking; besides, it achieves satisfactory robustness to uncertain model parameters and relatively large initial tracking errors. [Display omitted] • A robust event-triggered prescribed performance controller for PEM fuel cell systems. • Oxygen stoichiometry (OS) and stack temperature (ST) are simultaneously controlled. • Integral absolute errors when tracking OS and ST are 0.732 and 12.94 respectively. • A better compromise between control performance and communication cost. • The chattering and jump phenomena in control signals are suppressed. [ABSTRACT FROM AUTHOR]

Neural Networks (NNs) can be used for energy management of hybrid vehicles, but they are hard to tune in inference to adapt to different driving conditions. To make the NN-based energy management strategy more flexible, this paper proposes a controllable NN for optimal energy management of fuel cell hybrid electric vehicles. Inspired by the equivalent factor in the Equivalent Consumption Minimization Strategy (ECMS), we introduce an adjustable target variable for the final state as an input to the NN-based strategy. During training, classification and regression networks with single-step and multi-step inputs are considered. An efficient shooting method and an adaptive method are then introduced to realize the precise control of the final state and online parameter adaptation. Simulations of the proposed method and the benchmarking method are carried out in different battery discharge modes. Results demonstrate that the proposed shooting neural classifier can achieve 99.7% fuel optimality of dynamic programming in a similar computational time to the shooting ECMS, and the proposed adaptive neural classifier can adapt to different driving conditions and has better fuel economy than the adaptive ECMS. • A controllable neural model for energy management of fuel cell vehicles is proposed. • Neural regressors and classifiers are trained under single-step and multi-step inputs. • A shooting method and an adaptive method for neural models are proposed. • The proposed method is comprehensively analyzed and compared with benchmarks. [ABSTRACT FROM AUTHOR]

Hydrogen storage cylinder is an important component in high-pressure gaseous hydrogen (HPGH 2) storage system, and plays a key role in hydrogen-powered transportation including land vehicles, ships and aircrafts. Over the past decade, the number of hydrogen fuel cell vehicles (HFCVs) has rapidly increased worldwide. In order to promote the application of hydrogen storage cylinder, guide its design, manufacture, inspection and testing, a series of regulations, codes and standards have been issued. The Chinese national standard, GB/T 42612, for type IV hydrogen storage cylinders has also been issued. This paper first gives a brief overview to these regulations, codes and standards. Furthermore, the specifications including scope, category, filling cycles, service life, materials, design, manufacture, qualification tests and periodic inspections are analyzed and compared. Issues about evaluation method for hydrogen compatibility of non-metallic materials, welded joints of plastic liner, joint between boss and liner are also discussed. Notably, the performance requirements in GB/T 42612 are generally in accordance with the international ones, but the requirements of materials, design and manufacture are more detailed. • The regulations, codes and standards for on-board high-pressure hydrogen storage cylinders are compared. • An in-depth analysis of scope, category, filling cycles, service life, materials, design, manufacture, etc. is provided. • The requirements for materials, design and manufacture in GB/T 42612 are more detailed than the others. • NDT methods for welded joints of plastic liner and joints between plastic liner and metal boss need to be developed. • Effective periodic inspection methods other than visual inspection need to be further researched. [ABSTRACT FROM AUTHOR]

Fuel Cell Hybrid Electric Vehicles (FCHEV) use batteries and Photo Voltaic (PV) arrays to overcome Fuel Cell (FC) limitations like slow reaction times and low power densities. In a traditional power conversion system, three converters link FC, PV array, and battery to the output load. Despite using the FC, PV array, and battery, it has three inductors and several switches. Each switch also endures high voltage stress, possibly lowering power density and efficiency. This paper proposes a single-inductor multi-input converter (SI-MIC) that achieves 550 V as output where the input is variable. The fuzzy logic controller enables the integration of multiple power sources by selectively turning the ON and OFF switches in various operating modes. Fewer active switches during the powering process make it possible to employ semiconductors with a lower voltage. Thus, the converter generates high power with low conduction and switching losses. The state space model verifies the validity and stability of the converter under various operating modes. • Battery and PV array are integrated with the fuel cell using the single inductor multi-input converter (SI-MIC). • Fuzzy logic controller is used for switching the semiconductor devices for operating in various modes. • Battery can be charged and discharged in standby and normal operating modes. • Even if the input voltage fluctuates, the output voltage is always maintained at 550 V. [ABSTRACT FROM AUTHOR]

The world is still largely dependent on oil and natural gas for its energy requirements which are harmful to the environment; therefore, it is high time that we look for alternative technologies for our growing energy needs. One such emerging area is fuel cell technology which produces clean energy in the form of electrical power. Integrating a Metal Hydride Hydrogen Storage (MHHS) system with a fuel cell can help increase energy efficiency. The heat dissipated during hydrogen absorption in MHHS can be used in other applications. In this paper, energy and exergy analysis of a fuel cell-based integrated system is performed. The system presents a Reversible Proton Exchange Membrane Fuel Cell capable of working in dual modes, i.e., as an Electrolyser as well as a fuel cell. The MHHS and Vapour Absorption Refrigeration System (VARS) are coupled with a reversible fuel cell for hydrogen storage and cooling applications, respectively. While working in the fuel cell mode, maximum efficiency of 47.84% is evaluated at 80 °C. The system efficiency with and without the VARS system at 80 °C was 73.29% and 47.84%, respectively. On the contrary, in the electrolyzer mode, the maximum efficiency comes out to be 85.65%. The use of the MHHS system for hydrogen storage results in excess heat release, and as a result, the overall efficiency of the electrolyzer was increased to 94.05%. • Thermodynamic integration of PEMFC with MHHS and VARS is performed. • Effect of key parameters on fuel cell system performance is investigated. • System energy and exergy efficiency of 73.3% and 59.5% respectively are reported. • The proposed system can achieve maximum electrolyzer efficiency of 85.65%. • Maximum cooling output from vapour absorption system is found to be 60.56 kW. [ABSTRACT FROM AUTHOR]

In the modern world, zero-carbon society has become a new buzzword of the era. Many projects have been initiated to develop alternatives not only to the environmental crisis but also to the shortage of fossil fuels. With successful projects in automobile technology, hydrogen fuel is now being tested and utilized as a sustainable green fuel in the aviation sector which will lead to zero carbon emission in the future. From the mid-20th century to the early 21st numerous countries and companies have funded multimillion projects to develop hydrogen-fueled aircraft. Empirical data show positive results for various projects. Consequently, large companies are investing in various innovations undertaken by researchers under their supervision. Over time, the efficiency of hydrogen-fueled aircraft has improved but the lack of refueling stations, large production cost, and consolidated carbon market share have impeded the path of hydrogen fuel being commercialized. In addition, the Unmanned Aerial Vehicle (UAV) is another important element of the Aviation industry, Hydrogen started to be commonly used as an alternative fuel for heavy-duty drones using fuel cell technology. The purpose of this paper is to provide an overview of the chronological development of hydrogen-powered aircraft technology and potential aviation applications for hydrogen and fuel cell technology. Furthermore, the major barriers to widespread adoption of hydrogen technology in aviation are identified, as are future research opportunities. [Display omitted] • Hydrogen is extensively researched and acknowledged as a viable mainstream fuel option. • Hydrogen fuel is now being tested and utilized as a sustainable green fuel in the aviation sector. • Numerous countries and companies have funded multimillion projects to develop hydrogen-fueled aircraft. • Empirical data show positive results for various projects. • New engine modules have been designed to accommodate hydrogen fuel cells economically. [ABSTRACT FROM AUTHOR]

Nafion membrane is a commercial type of electrolyte membrane that is widely used in low-temperature fuel cells. Nafion membrane is expensive and allows fuel to crossover from anode to cathode. Therefore, it decreases fuel utilization and results in mixed potential at the cathode. Modifying the Nafion membrane and/or replacing it with non-Nafion-based materials has shown promising results in solving these problems. Graphene is a two-dimensional material with exceptional properties that positively affect the performance of several energy conversion/storage devices. With its large surface functional groups, graphene oxide exhibits considerable ionic conductivity with low fuel crossover. This paper reviews and discusses the recent progress in utilizing graphene or its derivatives as a blend with Nafion and non-Nafion based membranes as well as a standalone membrane in low-temperature fuel cells. Graphene or its derivatives possess a high potential as a standalone membrane or a composite membrane in the various low temperature fuel cells applications in terms of high ionic conductivity at low humidity and relevant high temperature, high thermal, mechanical, and chemical stabilities. This work summarizes the recent progress in utilizing graphene and its derivatives (graphene oxide and other doped graphene) in different types of fuel cells, whether as a standalone or as a modifier of the Nafion and non-Nafion based membranes. The review covers the usage of graphene and its derivatives in PEMFCs, DMFCs, anion exchange DMFCs, and MFCs. Furthermore, it elaborates on the science and the engineering aspects of utilizing graphene and its derivatives in different fuel cells. This work demonstrates the importance of the graphene and its derivatives in improving the performance of low temperature fuel cells. • GO promoted high water retention of the fuel cell's membrane. • GO has excellent mechanical, chemical, and thermal stability, and thus its polymer blends gain these properties. • The blends of the electrolyte polymer with GO decreases the fuel crossover. • Applying of graphene as a standalone membrane in PEMFC was summarized. • The performance of Nafion-based and non Nafion-based membranes modified with graphene in fuel cells was summarized. [ABSTRACT FROM AUTHOR]

This paper discusses the technical and economic feasibility of a renewable energy-based system, aimed to replace the traditional diesel engines implemented on a pushed and pusher bulk carrier barge. This barge has a challenging navigational route in the Nile River from Alexandria to Aswan and vice versa. It is scheduled to complete 30 trips annually while carrying 850 tons/trip. The system is based on photovoltaic panels, and was selected with its excess energy to be stored primarily in the form of H 2 gas through electrolysis, and batteries (i.e. Power to Gas technology) to be later converted back to electrical energy through fuel cells. Hence, an operation algorithm was formulated to optimize the performance of the system by defining operating modes that use solar energy, hydrogen energy, batteries, or hybrid energy coming from multiple sources that result in an internal rate of return (IRR) of 15.1% and overall efficiency of 57.9%. This high efficiency is due to the nature of water current that flows from south to north of Egypt, therefore, causing a significant reduction in power demand in the trip from Aswan to Alexandria that requires 11,980 kW h, compared to the trip from Alexandria to Aswan that requires 21,064 kW h. • Zero emission solution combining solar energy, hydrogen generation and fuel cell propulsion for a barge in Nile River. • Preparation to achieve the 7th goal of sustainable development ensuring green propulsion in Nile River cargo transport. • Efficient use of natural resources, solar energy and water current from south to north of Egypt. • Integrating electrolizer, fuel cell, solar energy pv, batteries, and hydrogen storage to form an autonomous barge. [ABSTRACT FROM AUTHOR]

In this communication, an experimental investigation is carried out on a PEM (Proton Exchange Membrane) fuel cell. A small-scale standalone PEM fuel cell system of 1 kW capacity is demonstrated in the present study. The fuel cell is connected to the charge controller, and the charge controller is further connected to the DC and AC loads to study the fuel cell characteristics. A battery bank backup is also provided to account for the stable power output from the fuel cell. The purpose of the study is to determine the fuel cell's performance when operated with resistive, AC, and DC loads (home appliances within the rated power range). The effect of hydrogen flow rates on the power output is also presented in this paper. The DC and AC loads are connected to the fuel cell setup to study the characteristics of the fuel cell. From the study, it can be observed that the performance of the fuel cell is better at higher flow rates of hydrogen. The experimental results showed that the maximum power obtained was 986.8 W at a hydrogen supply rate of 15 LPM. The maximum fuel cell efficiency was found to be 44% at the flow rate of 8 LPM. The charge controller efficiency reported for DC and AC load connections is 94.97% and 96.98%, respectively. The inverter efficiency was observed to increase with the current value, with the maximum value reaching around 98.86%. • Experimental results of a 1 kW small scale PEM fuel cell are presented. • Study explores the effect of resistive, AC and DC loads on fuel cell performance. • Maximum PEM stack efficiency is determined to be 44%. [ABSTRACT FROM AUTHOR]

Steam reforming of methanol is an effective way to provide an on-line hydrogen source for fuel cells. However, due to the poor utilization of the performance of the catalyst, the traditional reformer has the problems of slow start-up, low hydrogen production. Therefore, it is urgent to develop new catalyst loading methods to make full use of the performance of the catalyst. In this paper, a foamed metal with nano copper wire is used for methanol-reformer. The relevant experiments were carried out to investigate the hydrogen production performance of the foam copper reformer based on nano copper wire and the traditional impregnation method. The results showed that compared with the metal foam autocatalysis, the hydrogen concentration in the product of the nano-copper wire reformer could be increased by more than 8 times. What's more, the concentration of hydrogen in the product is twice that of the current widely used impregnation method. Furthermore, this method reduced the start-up time of the reformer. Meanwhile, the best working parameters of nano copper wire methanol-reformer were obtained through experiments. [Display omitted] • An efficient methanol reforming reactor catalyzed by nano copper wire was developed. • The concentration of hydrogen in the product of copper nanofiber foam was increased by more than two times. • Nano structured copper foam can greatly shorten the start-up time of the reformer. • There is an optimum working condition of nano copper wire reformer. [ABSTRACT FROM AUTHOR]

In a 100% renewable energy scenario, power generation fluctuates, requiring management and control of this generation. Storage is presented as a solution to regulate production discontinuity. In particular, seasonal storage can compensate for long-term fluctuations and serve as a necessary complement to short-term storage management. Due to the potential role of hydrogen in the decarbonization of energy production systems, this research attempts to analyse the levelized cost of storage (LCOS) of this energy carrier as a solution to long-term electricity requirements. The research focuses on the analysis of the total Power-to-Power (P2P) process cost, all factors affecting the input of electricity up to the output of electricity after the conversion of the hydrogen are considered. A transformation of the surplus electricity to hydrogen through a PEM electrolyzer is proposed in this paper. This hydrogen would be stored seasonally in salt caverns. Finally, a gas-to-energy transformation using gas turbines or fuel cells is contemplated. The analysis presents highly competitive results in terms of cost, demonstrating the system's competitiveness and potential: the turbine powered by 100% hydrogen solution appears to be more cost effective than the fuel cell solution: 0.207€/kWh and 0.284€/kWh respectively. Hydrogen storage presents itself as the most cost-effective long-term alternative in the near future, even better than pumped hydro, compressed air or batteries. • LCOS: Levelized Costs of Storage for a large-scale and long-term system. • The use of hydrogen as an energy carrier to store electrical energy from renewable sources at large scale. • Long-term storage of hydrogen in salt caverns. • Transformation of stored hydrogen into electricity through turbine and fuel cells. [ABSTRACT FROM AUTHOR]

Hydrogen fuel cell technology is one of the key focus areas to facilitate the transition from carbon-based fuels to more sustainable solutions in the transportation and mobile power sectors. Transient voltage fluctuations due to load changes and even operation of fuel cells with DC/DC and DC/AC converters are detrimental to the lifetime and this paper proposes a method to deal with these fluctuations. Adding electric field modifier (EFM) electrodes made of gold to the membrane of a fuel cell was proposed elsewhere as a way to influence the short term flux of charge carriers through the membrane. While electrochemical impedance spectroscopy shows a limited capacitance of such electrodes, experiments using square wave excitation of the system in the kHz frequency range show a promising reaction of the cell to this treatment. More in-depth analysis of the used electrode material reveals the need to insulate future EFM electrodes in order to prevent oxidative dissolution. However, this work shows that the principle of using EFM electrodes to manipulate transient oscillations is physically sound. • Square Wave excitation of EFMs shows effect on cell voltage. • EIS measurement provides specific capacity of gold EFM similar to literature value. • Cyclic Voltammetry measurements of gold mesh electrodes in Nafion, behaviour equivalent to gold in acid solution. • Scanning electron microscopy confirms oxidative dissolution of gold in membrane due to potential cycling. [ABSTRACT FROM AUTHOR]

This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project. • State machine-based supervisory controller for fuel cell system is designed. • The designed control structure is implemented in a prototype hydrogen-based vehicle. • The controller comprises: State Machine, Setpoint Generator, Power Limit Calculator. • The proposed control structure handles the startup and shutdown process of PEMFC. • Minimizing stack degradation by implementing a fuel cell power limit calculator. [ABSTRACT FROM AUTHOR]

Technological innovation is important to further reduce the cost of hydrogen fuel cells (HFC) and enhance commercial availability. Technology patents hydrogen fuel cell play an important role in understanding the trend of technological innovation and future policymaking. By extracting patent data of hydrogen fuel cells from IncoPat database between 2003 and 2022, the knowledge map of hydrogen fuel cell technology was drawn in this paper based on the statistical analysis method and IPC co-category analysis method. The results shows that: (1) From the technology life cycle trajectory, 2003–2013 is the initial stage of hydrogen fuel cell technology, and 2014–2022 is the rapid development period of hydrogen fuel cells. (2) Through mapping the knowledge map of hotspots in the hydrogen fuel cell technology field using IPC co-category analysis, knowledge map shows 849 nodes and 6116 connected lines, and the network density is 0.017. (3) From the hydrogen fuel cell technology clustering map, a total of nine hot topics were formed in 2003–2022, namely H01M8/04089, C08J5/22, H01M4/88, H01M8/0228, H01M8/10, C25B1/04, G01N27/12, F04D29/58, F17C13/02. (4) 59 significant IPCs were placed in the hydrogen fuel cell technology domain from 2003 to 2022. Moreover, the hydrogen fuel cell technology evolution can be divided into three phases, 2003–2008, 2008–2018, and 2018–2022, respectively. • Hydrogen fuel cell (HFC) patent show rapid development since 2017, with exponential growth. • H01 M is the prominent technical classification, particularly in battery pack technology. • Burst analysis identifies 59 significant IPCs, representing the forefront of HFC technology. • IPC analysis identifies research hotspots, such as gaseous reactants and manufacturing methods. • Knowledge evolution is divided into three phases: 2003–2008, 2008–2018, and 2018–2022. [ABSTRACT FROM AUTHOR]

Given the current maturity of hydrogen technologies, accurate and computationally efficient numerical models are crucial for improving their understanding and development. Traditional models are either computationally prohibitive or lack the capacity to assess the spatial distribution of critical variables. The present paper suggests a hybrid numerical model for Fuel Cells (FCs) and electrolysers, articulating the coupling between a 1D analytical model and a Computational Fluid Dynamics (CFD) model via a nonlinear regression. Results present an initial validation of the 1D analytical model and the CFD model, and, once the validation is proven successful, the hybrid model is evaluated with a relatively long and highly varying loading profile that covers a wide range of the potential operational points of a FC. The hybrid model shows promising results, showing fidelity levels similar to CFD models, including the capacity to assess the spatial distribution, and a low computational cost. Hence, this hybrid model is demonstrated to be an attractive tool for the design of FCs and electrolysers, optimisation of thermal management and control strategies, degradation analysis, and techno-economic analysis. [ABSTRACT FROM AUTHOR]

In order to ensure the safety of hydrogen refueling systems and fuel cell vehicles under various filling conditions, the filling parameters are usually set very conservatively, leading to waste energy consumption and investment. The lumped parameter hydrogen gas model and one-dimension tank wall model of the hydrogen filling process previously proposed by our team were extended and improved to the entire hydrogen refueling system by considering the Joule-Thomson effect, kinetic energy and using a more accurate model of the heat transfer coefficients between the inner tank wall and hydrogen gas and between the outer tank wall and ambient. Based on our validated model, the effects of constant and two-stage average pressure ramp rates (APRRs) and precooling/inlet temperatures on refueling performances were investigated, respectively. Compared with the optimal filling strategy of the reference paper, where a constant APRR is the best, our two-stage APRRs can further reduce the cooling power for various inlet temperatures without increasing the cooling energy. For example, maximum cooling power can be reduced by 23.8% at the inlet temperature of −20 °C. Compared with the previous research result obtained using a constant inlet temperature solved by the analytical solution, the two-stage inlet temperatures can further reduce the cooling power by 16.3% at an APRR of 0.428 MPa/s without increasing the cooling energy. • A thermodynamic model for a hydrogen refueling system is improved and well validated. • Joule-Thomson effect, kinetic energy and accurate heat transfer model are considered. • Effects of two-stage average pressure ramp rates and inlet temperatures are studied. • Two-stage strategies can reduce cooling power without increasing cooling energy. [ABSTRACT FROM AUTHOR]

Energy resources based on green hydrogen are nowadays beginning to enjoy wide adoption and draw considerable interest. There are different types of hydrogen production, but it is green hydrogen that is becoming an attractive energy development capable of replacing blue and grey hydrogen as well as fossil fuels, Thereby the carbon footprint will be reduced for a number of industrial processes. Proton exchange membrane electrolyzers used for the production of environmentally friendly hydrogen have one key shortcoming, which is the short service life of the equipment. This paper presents a comparative study of the commonly applied PLL control of AC-DC converters. To improve the control of the proton exchange membrane of the electrolyzer, a vector control arrangement is adopted, which allows, by relying on cascade control loops, maintaining different DC link voltage levels and thereby extending the DC link input voltage variation range. Process flow diagram of hydrogen production in the wind turbine. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper presents the results of research into improving the ionic conductivity of Molten Carbonate Fuel Cell by modifying the matrix material. So far, we have succeeded in using materials such as YSZ and SDC, but we are now trying to use powders based on Ba Na and TiO 2. These materials are characterized by their oxygen ion conductivity at elevated temperatures. A matrix of these materials was produced and used to build MCFCs. Based on the experiments carried out and the mathematical model of the fuel cell, the contribution of the oxygen ion conductivity to the total ionic conductivity was determined. • Research on oxygen ion conduction materials was performed. • BNT material has best oxygen ion conductivity parameters and was chosen for experiments. • New matrix made of BNT was manufactured. • Composite Li/K and BNT membrane was investigated under EIS and in fuel cell. • Model including ionic conductivity and tortuosity is presented and validated. [ABSTRACT FROM AUTHOR]

The use of fuel cell (FC) is considered one of the methods of producing electricity with relatively high efficiency. So, it has attracted many researchers' attention to develop and improve its performance. The present study deals with the technical-economic optimal design of a hybrid power generation system based on a Proton Exchange Membrane (PEM) FC combined with an Organic Rankine Cycle (ORC). ORC is used to recover the generated heat in PEM FC. The decision variables of this study include FC operating pressure and temperature, current density, FC area, the quantity of FC, and operating parameters of the ORC system, including HRVG PPTD, condenser PPTD, and refrigerant mass fraction in zeotropic mixture. In this study, three zeotropic mixtures, including R11-R245fa, R11-R123, and R123-R245fa, are studied as the working fluid of the ORC system. The objective functions considered to be optimized are the system's exergy efficiency and total cost rate (TCR). Finally, it is observed that the highest exergy efficiency is obtained using the zeotropic mixture R11-R245fa with a value of 54.15%, and the lowest TCR is obtained with the mixture R11-R123 with a value of 0.65 $/s. Zeotropic mixture R11-R123 has the exergoenvironmental index, environmental damage effectiveness index, and exergy stability factor of 0.5506, 1.277, and 0.4750, respectively. • A hybrid electricity generation system including PEM FC and ORC is analyzed. • Exergy Efficiency and economic analysis are considered for system evaluation. • Three novel zeotropic mixtures are examined as the working fluid of the ORC system. • A Parametric Study and optimization are conducted in this research paper. [ABSTRACT FROM AUTHOR]

In recent years, supervised deep learning-based methods have achieved significant results in fuel cell system fault diagnosis. However, most existing deep learning-based fault prediction methods suffer from missing fault labels and data limitations due to the difficulty in obtaining fault and degradation data in real fuel cell systems. To address the above challenges, this paper proposes a fault diagnosis method based on digital twin and unsupervised domain adaptive learning. The method has two key features: First, a maximum-relevance minimum-redundancy algorithm is used to select the input signals. Then a high-order fuel cell system model is developed to obtain a large amount of digital domain fault data at low cost by simulating fault injection. Second, domain-invariant features are extracted using a domain-adaptive adversarial learning approach to reduce the distribution differences between the digital and real domains. The method successfully diagnosed nine typical faults in the fuel cell air, hydrogen, and thermal subsystems without real data fault labels. Under dynamic load conditions, the diagnostic accuracy reached 92.5 %. In addition, the method achieves a diagnostic accuracy of over 90 % under domain adversarial training using only normal real data. The experimental results show that the proposed method can achieve fuel cell system fault diagnosis without fault labels and significantly reduce the dependence on fault data. [Display omitted] • An unsupervised fault diagnosis method for PEMFC systems is proposed. • The diagnostic algorithm is investigated for nine typical faults. • The training process of diagnostic framework does not require fault labels. • The algorithm still has high accuracy using only normal test data for training. [ABSTRACT FROM AUTHOR]